Dataset statistics
| Dataset A | Dataset B | |
|---|---|---|
| Number of variables | 12 | 12 |
| Number of observations | 446 | 446 |
| Missing cells | 439 | 431 |
| Missing cells (%) | 8.2% | 8.1% |
| Duplicate rows | 0 | 0 |
| Duplicate rows (%) | 0.0% | 0.0% |
| Total size in memory | 45.3 KiB | 45.3 KiB |
| Average record size in memory | 104.0 B | 104.0 B |
Variable types
| Dataset A | Dataset B | |
|---|---|---|
| Numeric | 5 | 5 |
| Categorical | 4 | 4 |
| Text | 3 | 3 |
| Dataset A | Dataset B | |
|---|---|---|
Survived is highly overall correlated with Sex | Survived is highly overall correlated with Sex | High Correlation |
Sex is highly overall correlated with Survived | Sex is highly overall correlated with Survived | High Correlation |
Age has 90 (20.2%) missing values | Age has 84 (18.8%) missing values | Missing |
Cabin has 347 (77.8%) missing values | Cabin has 346 (77.6%) missing values | Missing |
PassengerId has unique values | PassengerId has unique values | Unique |
Name has unique values | Name has unique values | Unique |
SibSp has 307 (68.8%) zeros | SibSp has 309 (69.3%) zeros | Zeros |
Parch has 338 (75.8%) zeros | Parch has 343 (76.9%) zeros | Zeros |
Fare has 8 (1.8%) zeros | Fare has 11 (2.5%) zeros | Zeros |
| Alert not present in this dataset | SibSp is highly overall correlated with Parch | High Correlation |
| Alert not present in this dataset | Parch is highly overall correlated with SibSp | High Correlation |
Reproduction
| Dataset A | Dataset B | |
|---|---|---|
| Analysis started | 2023-09-12 08:35:18.700398 | 2023-09-12 08:35:23.583917 |
| Analysis finished | 2023-09-12 08:35:23.582476 | 2023-09-12 08:35:27.435033 |
| Duration | 4.88 seconds | 3.85 seconds |
| Software version | ydata-profiling v0.0.dev0 | ydata-profiling v0.0.dev0 |
| Download configuration | config.json | config.json |
PassengerId
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 430.83857 | 452.16592 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 1 | 1 |
| Maximum | 891 | 891 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 1 | 1 |
| 5-th percentile | 42.25 | 51.5 |
| Q1 | 199.25 | 244.25 |
| median | 422 | 448.5 |
| Q3 | 659 | 678 |
| 95-th percentile | 842.75 | 838.75 |
| Maximum | 891 | 891 |
| Range | 890 | 890 |
| Interquartile range (IQR) | 459.75 | 433.75 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 261.04351 | 253.40065 |
| Coefficient of variation (CV) | 0.60589634 | 0.5604152 |
| Kurtosis | -1.2239694 | -1.1747123 |
| Mean | 430.83857 | 452.16592 |
| Median Absolute Deviation (MAD) | 228.5 | 217.5 |
| Skewness | 0.063354926 | -0.036099735 |
| Sum | 192154 | 201666 |
| Variance | 68143.713 | 64211.892 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 56 | 1 | 0.2% |
| 405 | 1 | 0.2% |
| 678 | 1 | 0.2% |
| 433 | 1 | 0.2% |
| 341 | 1 | 0.2% |
| 573 | 1 | 0.2% |
| 131 | 1 | 0.2% |
| 518 | 1 | 0.2% |
| 526 | 1 | 0.2% |
| 713 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 264 | 1 | 0.2% |
| 370 | 1 | 0.2% |
| 624 | 1 | 0.2% |
| 303 | 1 | 0.2% |
| 703 | 1 | 0.2% |
| 367 | 1 | 0.2% |
| 477 | 1 | 0.2% |
| 871 | 1 | 0.2% |
| 507 | 1 | 0.2% |
| 697 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 2 | 1 | |
| 5 | 1 | |
| 7 | 1 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 16 | 1 | |
| 17 | 1 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 5 | 1 | |
| 7 | 1 | |
| 9 | 1 | |
| 11 | 1 | |
| 14 | 1 | |
| 17 | 1 | |
| 18 | 1 | |
| 20 | 1 | |
| 22 | 1 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 5 | 1 | |
| 7 | 1 | |
| 9 | 1 | |
| 11 | 1 | |
| 14 | 1 | |
| 17 | 1 | |
| 18 | 1 | |
| 20 | 1 | |
| 22 | 1 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 2 | 1 | |
| 5 | 1 | |
| 7 | 1 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 16 | 1 | |
| 17 | 1 |
Survived
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 0 | |
|---|---|
| 1 |
| 0 | |
|---|---|
| 1 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 2 | 2 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 1 | 0 |
| 2nd row | 0 | 0 |
| 3rd row | 1 | 1 |
| 4th row | 1 | 1 |
| 5th row | 1 | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 446 |
| Value | Count | Frequency (%) |
| Common | 446 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 446 |
| Value | Count | Frequency (%) |
| ASCII | 446 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
| Value | Count | Frequency (%) |
| 0 | 268 | |
| 1 | 178 |
Pclass
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 3 | |
|---|---|
| 1 | |
| 2 |
| 3 | |
|---|---|
| 1 | |
| 2 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 1 | 1 |
| 2nd row | 3 | 1 |
| 3rd row | 2 | 3 |
| 4th row | 3 | 1 |
| 5th row | 1 | 3 |
Common Values
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 446 |
| Value | Count | Frequency (%) |
| Common | 446 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 446 |
| Value | Count | Frequency (%) |
| ASCII | 446 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 3 | 246 | |
| 1 | 104 | |
| 2 | 96 | 21.5% |
| Value | Count | Frequency (%) |
| 3 | 243 | |
| 1 | 107 | |
| 2 | 96 | 21.5% |
Name
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 67 | 57 |
| Median length | 48 | 48 |
| Mean length | 26.704036 | 26.784753 |
| Min length | 12 | 12 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 11910 | 11946 |
| Distinct characters | 60 | 60 |
| Distinct categories | 7 | 7 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 446 | 446 ? |
| Unique (%) | 100.0% | 100.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | Woolner, Mr. Hugh | Harrison, Mr. William |
| 2nd row | Johanson, Mr. Jakob Alfred | Smith, Mr. Richard William |
| 3rd row | Richards, Master. William Rowe | Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) |
| 4th row | Osman, Mrs. Mara | Graham, Miss. Margaret Edith |
| 5th row | Carter, Mr. William Ernest | O'Brien, Mr. Timothy |
| Value | Count | Frequency (%) |
| mr | 256 | 14.2% |
| miss | 104 | 5.8% |
| mrs | 58 | 3.2% |
| william | 32 | 1.8% |
| john | 25 | 1.4% |
| master | 21 | 1.2% |
| henry | 18 | 1.0% |
| mary | 13 | 0.7% |
| james | 13 | 0.7% |
| george | 11 | 0.6% |
| Other values (893) | 1250 |
| Value | Count | Frequency (%) |
| mr | 269 | 14.8% |
| miss | 84 | 4.6% |
| mrs | 65 | 3.6% |
| william | 38 | 2.1% |
| john | 23 | 1.3% |
| henry | 17 | 0.9% |
| master | 16 | 0.9% |
| charles | 15 | 0.8% |
| george | 15 | 0.8% |
| james | 13 | 0.7% |
| Other values (885) | 1259 |
Most occurring characters
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 957 | 8.0% |
| e | 853 | 7.2% |
| a | 820 | 6.9% |
| s | 665 | 5.6% |
| n | 661 | 5.5% |
| i | 655 | 5.5% |
| M | 575 | 4.8% |
| l | 508 | 4.3% |
| o | 496 | 4.2% |
| Other values (50) | 4364 |
| Value | Count | Frequency (%) |
| 1368 | 11.5% | |
| r | 977 | 8.2% |
| e | 849 | 7.1% |
| a | 806 | 6.7% |
| n | 673 | 5.6% |
| i | 661 | 5.5% |
| s | 614 | 5.1% |
| M | 562 | 4.7% |
| l | 530 | 4.4% |
| o | 501 | 4.2% |
| Other values (50) | 4405 |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 7651 | |
| Uppercase Letter | 1819 | 15.3% |
| Space Separator | 1356 | 11.4% |
| Other Punctuation | 950 | 8.0% |
| Close Punctuation | 62 | 0.5% |
| Open Punctuation | 62 | 0.5% |
| Dash Punctuation | 10 | 0.1% |
| Value | Count | Frequency (%) |
| Lowercase Letter | 7671 | |
| Uppercase Letter | 1823 | 15.3% |
| Space Separator | 1368 | 11.5% |
| Other Punctuation | 941 | 7.9% |
| Open Punctuation | 69 | 0.6% |
| Close Punctuation | 69 | 0.6% |
| Dash Punctuation | 5 | < 0.1% |
Most frequent character per category
Space Separator
| Value | Count | Frequency (%) |
| 1356 |
| Value | Count | Frequency (%) |
| 1368 |
Lowercase Letter
| Value | Count | Frequency (%) |
| r | 957 | |
| e | 853 | |
| a | 820 | |
| s | 665 | |
| n | 661 | |
| i | 655 | |
| l | 508 | 6.6% |
| o | 496 | 6.5% |
| t | 337 | 4.4% |
| h | 244 | 3.2% |
| Other values (16) | 1455 |
| Value | Count | Frequency (%) |
| r | 977 | |
| e | 849 | |
| a | 806 | |
| n | 673 | |
| i | 661 | |
| s | 614 | |
| l | 530 | 6.9% |
| o | 501 | 6.5% |
| t | 338 | 4.4% |
| h | 276 | 3.6% |
| Other values (16) | 1446 |
Uppercase Letter
| Value | Count | Frequency (%) |
| M | 575 | |
| A | 127 | 7.0% |
| J | 112 | 6.2% |
| H | 106 | 5.8% |
| C | 95 | 5.2% |
| S | 93 | 5.1% |
| E | 74 | 4.1% |
| W | 71 | 3.9% |
| B | 64 | 3.5% |
| L | 61 | 3.4% |
| Other values (15) | 441 |
| Value | Count | Frequency (%) |
| M | 562 | |
| A | 122 | 6.7% |
| J | 112 | 6.1% |
| H | 100 | 5.5% |
| S | 92 | 5.0% |
| E | 88 | 4.8% |
| C | 87 | 4.8% |
| W | 83 | 4.6% |
| G | 69 | 3.8% |
| B | 61 | 3.3% |
| Other values (15) | 447 |
Other Punctuation
| Value | Count | Frequency (%) |
| , | 446 | |
| . | 446 | |
| " | 54 | 5.7% |
| ' | 3 | 0.3% |
| / | 1 | 0.1% |
| Value | Count | Frequency (%) |
| , | 446 | |
| . | 446 | |
| " | 44 | 4.7% |
| ' | 4 | 0.4% |
| / | 1 | 0.1% |
Close Punctuation
| Value | Count | Frequency (%) |
| ) | 62 |
| Value | Count | Frequency (%) |
| ) | 69 |
Open Punctuation
| Value | Count | Frequency (%) |
| ( | 62 |
| Value | Count | Frequency (%) |
| ( | 69 |
Dash Punctuation
| Value | Count | Frequency (%) |
| - | 10 |
| Value | Count | Frequency (%) |
| - | 5 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 9470 | |
| Common | 2440 | 20.5% |
| Value | Count | Frequency (%) |
| Latin | 9494 | |
| Common | 2452 | 20.5% |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 1356 | ||
| , | 446 | 18.3% |
| . | 446 | 18.3% |
| ) | 62 | 2.5% |
| ( | 62 | 2.5% |
| " | 54 | 2.2% |
| - | 10 | 0.4% |
| ' | 3 | 0.1% |
| / | 1 | < 0.1% |
| Value | Count | Frequency (%) |
| 1368 | ||
| , | 446 | 18.2% |
| . | 446 | 18.2% |
| ( | 69 | 2.8% |
| ) | 69 | 2.8% |
| " | 44 | 1.8% |
| - | 5 | 0.2% |
| ' | 4 | 0.2% |
| / | 1 | < 0.1% |
Latin
| Value | Count | Frequency (%) |
| r | 957 | 10.1% |
| e | 853 | 9.0% |
| a | 820 | 8.7% |
| s | 665 | 7.0% |
| n | 661 | 7.0% |
| i | 655 | 6.9% |
| M | 575 | 6.1% |
| l | 508 | 5.4% |
| o | 496 | 5.2% |
| t | 337 | 3.6% |
| Other values (41) | 2943 |
| Value | Count | Frequency (%) |
| r | 977 | 10.3% |
| e | 849 | 8.9% |
| a | 806 | 8.5% |
| n | 673 | 7.1% |
| i | 661 | 7.0% |
| s | 614 | 6.5% |
| M | 562 | 5.9% |
| l | 530 | 5.6% |
| o | 501 | 5.3% |
| t | 338 | 3.6% |
| Other values (41) | 2983 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 11910 |
| Value | Count | Frequency (%) |
| ASCII | 11946 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 957 | 8.0% |
| e | 853 | 7.2% |
| a | 820 | 6.9% |
| s | 665 | 5.6% |
| n | 661 | 5.5% |
| i | 655 | 5.5% |
| M | 575 | 4.8% |
| l | 508 | 4.3% |
| o | 496 | 4.2% |
| Other values (50) | 4364 |
| Value | Count | Frequency (%) |
| 1368 | 11.5% | |
| r | 977 | 8.2% |
| e | 849 | 7.1% |
| a | 806 | 6.7% |
| n | 673 | 5.6% |
| i | 661 | 5.5% |
| s | 614 | 5.1% |
| M | 562 | 4.7% |
| l | 530 | 4.4% |
| o | 501 | 4.2% |
| Other values (50) | 4405 |
Sex
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| male | |
|---|---|
| female |
| male | |
|---|---|
| female |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 6 | 6 |
| Median length | 4 | 4 |
| Mean length | 4.7264574 | 4.67713 |
| Min length | 4 | 4 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 2108 | 2086 |
| Distinct characters | 5 | 5 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | male | male |
| 2nd row | male | male |
| 3rd row | male | female |
| 4th row | female | female |
| 5th row | male | male |
Common Values
| Value | Count | Frequency (%) |
| male | 284 | |
| female | 162 |
| Value | Count | Frequency (%) |
| male | 295 | |
| female | 151 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| male | 284 | |
| female | 162 |
| Value | Count | Frequency (%) |
| male | 295 | |
| female | 151 |
Most occurring characters
| Value | Count | Frequency (%) |
| e | 608 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 162 | 7.7% |
| Value | Count | Frequency (%) |
| e | 597 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 151 | 7.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 2108 |
| Value | Count | Frequency (%) |
| Lowercase Letter | 2086 |
Most frequent character per category
Lowercase Letter
| Value | Count | Frequency (%) |
| e | 608 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 162 | 7.7% |
| Value | Count | Frequency (%) |
| e | 597 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 151 | 7.2% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 2108 |
| Value | Count | Frequency (%) |
| Latin | 2086 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| e | 608 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 162 | 7.7% |
| Value | Count | Frequency (%) |
| e | 597 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 151 | 7.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 2108 |
| Value | Count | Frequency (%) |
| ASCII | 2086 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| e | 608 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 162 | 7.7% |
| Value | Count | Frequency (%) |
| e | 597 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 151 | 7.2% |
Age
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 76 | 70 |
| Distinct (%) | 21.3% | 19.3% |
| Missing | 90 | 84 |
| Missing (%) | 20.2% | 18.8% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 29.743202 | 30.995387 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.75 | 0.67 |
| Maximum | 74 | 80 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.75 | 0.67 |
| 5-th percentile | 4 | 4.05 |
| Q1 | 20.75 | 21 |
| median | 28 | 30 |
| Q3 | 38 | 39 |
| 95-th percentile | 56.25 | 58.95 |
| Maximum | 74 | 80 |
| Range | 73.25 | 79.33 |
| Interquartile range (IQR) | 17.25 | 18 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 14.934172 | 14.914041 |
| Coefficient of variation (CV) | 0.50210372 | 0.48116971 |
| Kurtosis | 0.12780732 | 0.17071811 |
| Mean | 29.743202 | 30.995387 |
| Median Absolute Deviation (MAD) | 8 | 9 |
| Skewness | 0.4312631 | 0.37901609 |
| Sum | 10588.58 | 11220.33 |
| Variance | 223.02951 | 222.42863 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 24 | 20 | 4.5% |
| 21 | 16 | 3.6% |
| 22 | 16 | 3.6% |
| 28 | 15 | 3.4% |
| 36 | 12 | 2.7% |
| 18 | 12 | 2.7% |
| 30 | 12 | 2.7% |
| 31 | 11 | 2.5% |
| 16 | 11 | 2.5% |
| 32 | 11 | 2.5% |
| Other values (66) | 220 | |
| (Missing) | 90 |
| Value | Count | Frequency (%) |
| 30 | 16 | 3.6% |
| 28 | 15 | 3.4% |
| 24 | 15 | 3.4% |
| 19 | 13 | 2.9% |
| 36 | 13 | 2.9% |
| 32 | 12 | 2.7% |
| 22 | 12 | 2.7% |
| 18 | 12 | 2.7% |
| 34 | 11 | 2.5% |
| 25 | 11 | 2.5% |
| Other values (60) | 232 | |
| (Missing) | 84 | 18.8% |
| Value | Count | Frequency (%) |
| 0.75 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 4 | |
| 2 | 6 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 2 | 0.4% |
| 8 | 3 | |
| 9 | 5 |
| Value | Count | Frequency (%) |
| 0.67 | 1 | 0.2% |
| 0.75 | 2 | 0.4% |
| 0.83 | 2 | 0.4% |
| 1 | 1 | 0.2% |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 3 | |
| 7 | 1 | 0.2% |
| 8 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0.67 | 1 | 0.2% |
| 0.75 | 2 | 0.4% |
| 0.83 | 2 | 0.4% |
| 1 | 1 | 0.2% |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 3 | |
| 7 | 1 | 0.2% |
| 8 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0.75 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 4 | |
| 2 | 6 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 2 | 0.4% |
| 8 | 3 | |
| 9 | 5 |
SibSp
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 7 | 7 |
| Distinct (%) | 1.6% | 1.6% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.57623318 | 0.47309417 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 8 | 8 |
| Zeros | 307 | 309 |
| Zeros (%) | 68.8% | 69.3% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 1 | 1 |
| 95-th percentile | 3 | 2 |
| Maximum | 8 | 8 |
| Range | 8 | 8 |
| Interquartile range (IQR) | 1 | 1 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 1.2815967 | 1.0180143 |
| Coefficient of variation (CV) | 2.2240938 | 2.1518217 |
| Kurtosis | 16.788616 | 22.019084 |
| Mean | 0.57623318 | 0.47309417 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 3.7383769 | 4.0207869 |
| Sum | 257 | 211 |
| Variance | 1.64249 | 1.0363531 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 96 | 21.5% |
| 2 | 15 | 3.4% |
| 4 | 10 | 2.2% |
| 3 | 10 | 2.2% |
| 8 | 7 | 1.6% |
| 5 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 309 | |
| 1 | 107 | 24.0% |
| 2 | 11 | 2.5% |
| 3 | 8 | 1.8% |
| 4 | 6 | 1.3% |
| 8 | 3 | 0.7% |
| 5 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 96 | 21.5% |
| 2 | 15 | 3.4% |
| 3 | 10 | 2.2% |
| 4 | 10 | 2.2% |
| 5 | 1 | 0.2% |
| 8 | 7 | 1.6% |
| Value | Count | Frequency (%) |
| 0 | 309 | |
| 1 | 107 | 24.0% |
| 2 | 11 | 2.5% |
| 3 | 8 | 1.8% |
| 4 | 6 | 1.3% |
| 5 | 2 | 0.4% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 309 | |
| 1 | 107 | 24.0% |
| 2 | 11 | 2.5% |
| 3 | 8 | 1.8% |
| 4 | 6 | 1.3% |
| 5 | 2 | 0.4% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 96 | 21.5% |
| 2 | 15 | 3.4% |
| 3 | 10 | 2.2% |
| 4 | 10 | 2.2% |
| 5 | 1 | 0.2% |
| 8 | 7 | 1.6% |
Parch
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 6 | 7 |
| Distinct (%) | 1.3% | 1.6% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.37892377 | 0.36995516 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 5 | 6 |
| Zeros | 338 | 343 |
| Zeros (%) | 75.8% | 76.9% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 0 | 0 |
| 95-th percentile | 2 | 2 |
| Maximum | 5 | 6 |
| Range | 5 | 6 |
| Interquartile range (IQR) | 0 | 0 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 0.78319697 | 0.82374508 |
| Coefficient of variation (CV) | 2.0668985 | 2.2266079 |
| Kurtosis | 8.7253408 | 12.42968 |
| Mean | 0.37892377 | 0.36995516 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 2.6051505 | 3.0986322 |
| Sum | 169 | 165 |
| Variance | 0.61339749 | 0.67855595 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=6)
| Value | Count | Frequency (%) |
| 0 | 338 | |
| 1 | 60 | 13.5% |
| 2 | 42 | 9.4% |
| 5 | 3 | 0.7% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 343 | |
| 1 | 61 | 13.7% |
| 2 | 33 | 7.4% |
| 5 | 3 | 0.7% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 338 | |
| 1 | 60 | 13.5% |
| 2 | 42 | 9.4% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| 5 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 343 | |
| 1 | 61 | 13.7% |
| 2 | 33 | 7.4% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 5 | 3 | 0.7% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 343 | |
| 1 | 61 | 13.7% |
| 2 | 33 | 7.4% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 5 | 3 | 0.7% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 338 | |
| 1 | 60 | 13.5% |
| 2 | 42 | 9.4% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| 5 | 3 | 0.7% |
Ticket
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 372 | 383 |
| Distinct (%) | 83.4% | 85.9% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 18 | 18 |
| Median length | 17 | 17 |
| Mean length | 6.8340807 | 6.8632287 |
| Min length | 4 | 3 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 3048 | 3061 |
| Distinct characters | 32 | 35 |
| Distinct categories | 5 | 5 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 321 | 337 ? |
| Unique (%) | 72.0% | 75.6% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 19947 | 112059 |
| 2nd row | 3101264 | 113056 |
| 3rd row | 29106 | STON/O2. 3101279 |
| 4th row | 349244 | 112053 |
| 5th row | 113760 | 330979 |
| Value | Count | Frequency (%) |
| pc | 35 | 6.1% |
| c.a | 18 | 3.1% |
| ca | 9 | 1.6% |
| a/5 | 9 | 1.6% |
| 2343 | 7 | 1.2% |
| sc/paris | 7 | 1.2% |
| 2 | 6 | 1.0% |
| ston/o | 6 | 1.0% |
| 347082 | 6 | 1.0% |
| w./c | 5 | 0.9% |
| Other values (388) | 468 |
| Value | Count | Frequency (%) |
| pc | 26 | 4.6% |
| c.a | 11 | 1.9% |
| ston/o | 10 | 1.8% |
| 2 | 10 | 1.8% |
| a/5 | 7 | 1.2% |
| ca | 6 | 1.1% |
| soton/oq | 6 | 1.1% |
| 1601 | 5 | 0.9% |
| ston/o2 | 5 | 0.9% |
| w./c | 5 | 0.9% |
| Other values (401) | 477 |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 366 | |
| 1 | 315 | |
| 2 | 313 | |
| 4 | 240 | 7.9% |
| 7 | 236 | 7.7% |
| 6 | 229 | 7.5% |
| 5 | 195 | 6.4% |
| 0 | 189 | 6.2% |
| 9 | 170 | 5.6% |
| 8 | 141 | 4.6% |
| Other values (22) | 654 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 330 | |
| 2 | 299 | |
| 7 | 238 | 7.8% |
| 4 | 235 | 7.7% |
| 6 | 222 | 7.3% |
| 0 | 216 | 7.1% |
| 5 | 197 | 6.4% |
| 9 | 164 | 5.4% |
| 8 | 148 | 4.8% |
| Other values (25) | 631 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 2394 | |
| Uppercase Letter | 347 | 11.4% |
| Other Punctuation | 164 | 5.4% |
| Space Separator | 130 | 4.3% |
| Lowercase Letter | 13 | 0.4% |
| Value | Count | Frequency (%) |
| Decimal Number | 2430 | |
| Uppercase Letter | 349 | 11.4% |
| Other Punctuation | 147 | 4.8% |
| Space Separator | 122 | 4.0% |
| Lowercase Letter | 13 | 0.4% |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 3 | 366 | |
| 1 | 315 | |
| 2 | 313 | |
| 4 | 240 | |
| 7 | 236 | |
| 6 | 229 | |
| 5 | 195 | |
| 0 | 189 | |
| 9 | 170 | |
| 8 | 141 | 5.9% |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 330 | |
| 2 | 299 | |
| 7 | 238 | |
| 4 | 235 | |
| 6 | 222 | |
| 0 | 216 | |
| 5 | 197 | |
| 9 | 164 | |
| 8 | 148 | 6.1% |
Space Separator
| Value | Count | Frequency (%) |
| 130 |
| Value | Count | Frequency (%) |
| 122 |
Other Punctuation
| Value | Count | Frequency (%) |
| . | 117 | |
| / | 47 |
| Value | Count | Frequency (%) |
| . | 95 | |
| / | 52 |
Uppercase Letter
| Value | Count | Frequency (%) |
| C | 90 | |
| P | 58 | |
| A | 49 | |
| O | 42 | |
| S | 41 | |
| N | 17 | 4.9% |
| T | 15 | 4.3% |
| I | 8 | 2.3% |
| W | 7 | 2.0% |
| R | 6 | 1.7% |
| Other values (5) | 14 | 4.0% |
| Value | Count | Frequency (%) |
| O | 70 | |
| C | 68 | |
| P | 41 | |
| S | 40 | |
| A | 32 | |
| N | 30 | |
| T | 27 | 7.7% |
| Q | 11 | 3.2% |
| W | 9 | 2.6% |
| E | 5 | 1.4% |
| Other values (6) | 16 | 4.6% |
Lowercase Letter
| Value | Count | Frequency (%) |
| a | 4 | |
| s | 3 | |
| i | 3 | |
| r | 3 |
| Value | Count | Frequency (%) |
| a | 4 | |
| s | 3 | |
| r | 2 | |
| i | 2 | |
| l | 1 | 7.7% |
| e | 1 | 7.7% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 2688 | |
| Latin | 360 | 11.8% |
| Value | Count | Frequency (%) |
| Common | 2699 | |
| Latin | 362 | 11.8% |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 3 | 366 | |
| 1 | 315 | |
| 2 | 313 | |
| 4 | 240 | |
| 7 | 236 | |
| 6 | 229 | |
| 5 | 195 | |
| 0 | 189 | |
| 9 | 170 | |
| 8 | 141 | 5.2% |
| Other values (3) | 294 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 330 | |
| 2 | 299 | |
| 7 | 238 | |
| 4 | 235 | |
| 6 | 222 | |
| 0 | 216 | |
| 5 | 197 | |
| 9 | 164 | |
| 8 | 148 | 5.5% |
| Other values (3) | 269 |
Latin
| Value | Count | Frequency (%) |
| C | 90 | |
| P | 58 | |
| A | 49 | |
| O | 42 | |
| S | 41 | |
| N | 17 | 4.7% |
| T | 15 | 4.2% |
| I | 8 | 2.2% |
| W | 7 | 1.9% |
| R | 6 | 1.7% |
| Other values (9) | 27 | 7.5% |
| Value | Count | Frequency (%) |
| O | 70 | |
| C | 68 | |
| P | 41 | |
| S | 40 | |
| A | 32 | |
| N | 30 | |
| T | 27 | 7.5% |
| Q | 11 | 3.0% |
| W | 9 | 2.5% |
| E | 5 | 1.4% |
| Other values (12) | 29 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 3048 |
| Value | Count | Frequency (%) |
| ASCII | 3061 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 3 | 366 | |
| 1 | 315 | |
| 2 | 313 | |
| 4 | 240 | 7.9% |
| 7 | 236 | 7.7% |
| 6 | 229 | 7.5% |
| 5 | 195 | 6.4% |
| 0 | 189 | 6.2% |
| 9 | 170 | 5.6% |
| 8 | 141 | 4.6% |
| Other values (22) | 654 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 330 | |
| 2 | 299 | |
| 7 | 238 | 7.8% |
| 4 | 235 | 7.7% |
| 6 | 222 | 7.3% |
| 0 | 216 | 7.1% |
| 5 | 197 | 6.4% |
| 9 | 164 | 5.4% |
| 8 | 148 | 4.8% |
| Other values (25) | 631 |
Fare
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 185 | 165 |
| Distinct (%) | 41.5% | 37.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 32.128287 | 30.313593 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 512.3292 | 512.3292 |
| Zeros | 8 | 11 |
| Zeros (%) | 1.8% | 2.5% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 7.22605 | 7.0542 |
| Q1 | 8.05 | 7.8958 |
| median | 15.3729 | 13.5 |
| Q3 | 31.275 | 29.125 |
| 95-th percentile | 113.275 | 110.38748 |
| Maximum | 512.3292 | 512.3292 |
| Range | 512.3292 | 512.3292 |
| Interquartile range (IQR) | 23.225 | 21.2292 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 46.498004 | 45.815062 |
| Coefficient of variation (CV) | 1.4472606 | 1.5113703 |
| Kurtosis | 31.090155 | 33.330745 |
| Mean | 32.128287 | 30.313593 |
| Median Absolute Deviation (MAD) | 7.6229 | 6.2708 |
| Skewness | 4.4807818 | 4.6638107 |
| Sum | 14329.216 | 13519.862 |
| Variance | 2162.0644 | 2099.0199 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 13 | 22 | 4.9% |
| 7.8958 | 19 | 4.3% |
| 8.05 | 18 | 4.0% |
| 10.5 | 16 | 3.6% |
| 7.75 | 15 | 3.4% |
| 26 | 13 | 2.9% |
| 16.1 | 8 | 1.8% |
| 0 | 8 | 1.8% |
| 26.55 | 8 | 1.8% |
| 7.8542 | 8 | 1.8% |
| Other values (175) | 311 |
| Value | Count | Frequency (%) |
| 8.05 | 24 | 5.4% |
| 13 | 23 | 5.2% |
| 7.75 | 20 | 4.5% |
| 26 | 17 | 3.8% |
| 7.8958 | 15 | 3.4% |
| 10.5 | 14 | 3.1% |
| 7.925 | 13 | 2.9% |
| 0 | 11 | 2.5% |
| 26.55 | 9 | 2.0% |
| 7.225 | 8 | 1.8% |
| Other values (155) | 292 |
| Value | Count | Frequency (%) |
| 0 | 8 | |
| 6.2375 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 2 | 0.4% |
| 7.0542 | 1 | 0.2% |
| 7.125 | 1 | 0.2% |
| 7.1417 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 11 | |
| 4.0125 | 1 | 0.2% |
| 5 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 2 | 0.4% |
| 7.05 | 5 | |
| 7.0542 | 2 | 0.4% |
| 7.125 | 2 | 0.4% |
| 7.1417 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 11 | |
| 4.0125 | 1 | 0.2% |
| 5 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 2 | 0.4% |
| 7.05 | 5 | |
| 7.0542 | 2 | 0.4% |
| 7.125 | 2 | 0.4% |
| 7.1417 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 8 | |
| 6.2375 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 2 | 0.4% |
| 7.0542 | 1 | 0.2% |
| 7.125 | 1 | 0.2% |
| 7.1417 | 1 | 0.2% |
Cabin
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 85 | 89 |
| Distinct (%) | 85.9% | 89.0% |
| Missing | 347 | 346 |
| Missing (%) | 77.8% | 77.6% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 15 | 11 |
| Median length | 3 | 3 |
| Mean length | 3.4242424 | 3.45 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 339 | 345 |
| Distinct characters | 19 | 18 |
| Distinct categories | 3 | 3 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 71 | 79 ? |
| Unique (%) | 71.7% | 79.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | C52 | B94 |
| 2nd row | B96 B98 | A19 |
| 3rd row | C91 | B42 |
| 4th row | D20 | G6 |
| 5th row | B96 B98 | E46 |
| Value | Count | Frequency (%) |
| c52 | 2 | 1.8% |
| e24 | 2 | 1.8% |
| e67 | 2 | 1.8% |
| f | 2 | 1.8% |
| c124 | 2 | 1.8% |
| d20 | 2 | 1.8% |
| b98 | 2 | 1.8% |
| b28 | 2 | 1.8% |
| e121 | 2 | 1.8% |
| b96 | 2 | 1.8% |
| Other values (84) | 91 |
| Value | Count | Frequency (%) |
| c23 | 3 | 2.6% |
| c27 | 3 | 2.6% |
| c25 | 3 | 2.6% |
| b96 | 2 | 1.8% |
| c125 | 2 | 1.8% |
| g6 | 2 | 1.8% |
| c52 | 2 | 1.8% |
| b98 | 2 | 1.8% |
| f | 2 | 1.8% |
| d35 | 2 | 1.8% |
| Other values (87) | 91 |
Most occurring characters
| Value | Count | Frequency (%) |
| 2 | 34 | 10.0% |
| 1 | 30 | 8.8% |
| B | 30 | 8.8% |
| C | 28 | 8.3% |
| 6 | 25 | 7.4% |
| 3 | 22 | 6.5% |
| 0 | 21 | 6.2% |
| 5 | 20 | 5.9% |
| 8 | 20 | 5.9% |
| D | 18 | 5.3% |
| Other values (9) | 91 |
| Value | Count | Frequency (%) |
| 2 | 41 | |
| C | 37 | |
| 3 | 30 | 8.7% |
| B | 28 | 8.1% |
| 5 | 24 | 7.0% |
| 6 | 23 | 6.7% |
| 1 | 21 | 6.1% |
| D | 19 | 5.5% |
| 9 | 18 | 5.2% |
| 4 | 17 | 4.9% |
| Other values (8) | 87 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 216 | |
| Uppercase Letter | 111 | |
| Space Separator | 12 | 3.5% |
| Value | Count | Frequency (%) |
| Decimal Number | 217 | |
| Uppercase Letter | 114 | |
| Space Separator | 14 | 4.1% |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 2 | 34 | |
| 1 | 30 | |
| 6 | 25 | |
| 3 | 22 | |
| 0 | 21 | |
| 5 | 20 | |
| 8 | 20 | |
| 4 | 16 | |
| 9 | 15 | |
| 7 | 13 | 6.0% |
| Value | Count | Frequency (%) |
| 2 | 41 | |
| 3 | 30 | |
| 5 | 24 | |
| 6 | 23 | |
| 1 | 21 | |
| 9 | 18 | |
| 4 | 17 | |
| 7 | 16 | 7.4% |
| 0 | 14 | 6.5% |
| 8 | 13 | 6.0% |
Uppercase Letter
| Value | Count | Frequency (%) |
| B | 30 | |
| C | 28 | |
| D | 18 | |
| E | 17 | |
| A | 8 | 7.2% |
| F | 6 | 5.4% |
| G | 3 | 2.7% |
| T | 1 | 0.9% |
| Value | Count | Frequency (%) |
| C | 37 | |
| B | 28 | |
| D | 19 | |
| E | 13 | 11.4% |
| A | 8 | 7.0% |
| F | 5 | 4.4% |
| G | 4 | 3.5% |
Space Separator
| Value | Count | Frequency (%) |
| 12 |
| Value | Count | Frequency (%) |
| 14 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 228 | |
| Latin | 111 |
| Value | Count | Frequency (%) |
| Common | 231 | |
| Latin | 114 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 2 | 34 | |
| 1 | 30 | |
| 6 | 25 | |
| 3 | 22 | |
| 0 | 21 | |
| 5 | 20 | |
| 8 | 20 | |
| 4 | 16 | |
| 9 | 15 | |
| 7 | 13 | 5.7% |
| Value | Count | Frequency (%) |
| 2 | 41 | |
| 3 | 30 | |
| 5 | 24 | |
| 6 | 23 | |
| 1 | 21 | |
| 9 | 18 | |
| 4 | 17 | |
| 7 | 16 | 6.9% |
| 0 | 14 | 6.1% |
| 14 | 6.1% |
Latin
| Value | Count | Frequency (%) |
| B | 30 | |
| C | 28 | |
| D | 18 | |
| E | 17 | |
| A | 8 | 7.2% |
| F | 6 | 5.4% |
| G | 3 | 2.7% |
| T | 1 | 0.9% |
| Value | Count | Frequency (%) |
| C | 37 | |
| B | 28 | |
| D | 19 | |
| E | 13 | 11.4% |
| A | 8 | 7.0% |
| F | 5 | 4.4% |
| G | 4 | 3.5% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 339 |
| Value | Count | Frequency (%) |
| ASCII | 345 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 2 | 34 | 10.0% |
| 1 | 30 | 8.8% |
| B | 30 | 8.8% |
| C | 28 | 8.3% |
| 6 | 25 | 7.4% |
| 3 | 22 | 6.5% |
| 0 | 21 | 6.2% |
| 5 | 20 | 5.9% |
| 8 | 20 | 5.9% |
| D | 18 | 5.3% |
| Other values (9) | 91 |
| Value | Count | Frequency (%) |
| 2 | 41 | |
| C | 37 | |
| 3 | 30 | 8.7% |
| B | 28 | 8.1% |
| 5 | 24 | 7.0% |
| 6 | 23 | 6.7% |
| 1 | 21 | 6.1% |
| D | 19 | 5.5% |
| 9 | 18 | 5.2% |
| 4 | 17 | 4.9% |
| Other values (8) | 87 |
Embarked
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 2 | 1 |
| Missing (%) | 0.4% | 0.2% |
| Memory size | 7.0 KiB | 7.0 KiB |
| S | |
|---|---|
| C | |
| Q | 32 |
| S | |
|---|---|
| C | |
| Q |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 444 | 445 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | S | S |
| 2nd row | S | S |
| 3rd row | S | S |
| 4th row | S | S |
| 5th row | S | Q |
Common Values
| Value | Count | Frequency (%) |
| S | 323 | |
| C | 89 | 20.0% |
| Q | 32 | 7.2% |
| (Missing) | 2 | 0.4% |
| Value | Count | Frequency (%) |
| S | 340 | |
| C | 64 | 14.3% |
| Q | 41 | 9.2% |
| (Missing) | 1 | 0.2% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| s | 323 | |
| c | 89 | 20.0% |
| q | 32 | 7.2% |
| Value | Count | Frequency (%) |
| s | 340 | |
| c | 64 | 14.4% |
| q | 41 | 9.2% |
Most occurring characters
| Value | Count | Frequency (%) |
| S | 323 | |
| C | 89 | 20.0% |
| Q | 32 | 7.2% |
| Value | Count | Frequency (%) |
| S | 340 | |
| C | 64 | 14.4% |
| Q | 41 | 9.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Uppercase Letter | 444 |
| Value | Count | Frequency (%) |
| Uppercase Letter | 445 |
Most frequent character per category
Uppercase Letter
| Value | Count | Frequency (%) |
| S | 323 | |
| C | 89 | 20.0% |
| Q | 32 | 7.2% |
| Value | Count | Frequency (%) |
| S | 340 | |
| C | 64 | 14.4% |
| Q | 41 | 9.2% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 444 |
| Value | Count | Frequency (%) |
| Latin | 445 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| S | 323 | |
| C | 89 | 20.0% |
| Q | 32 | 7.2% |
| Value | Count | Frequency (%) |
| S | 340 | |
| C | 64 | 14.4% |
| Q | 41 | 9.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 444 |
| Value | Count | Frequency (%) |
| ASCII | 445 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| S | 323 | |
| C | 89 | 20.0% |
| Q | 32 | 7.2% |
| Value | Count | Frequency (%) |
| S | 340 | |
| C | 64 | 14.4% |
| Q | 41 | 9.2% |
Dataset A
Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
Dataset A
Dataset B
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Dataset B
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Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
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Dataset B
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Dataset B
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Dataset B
Dataset A
| PassengerId | Age | SibSp | Parch | Fare | Survived | Pclass | Sex | Embarked | |
|---|---|---|---|---|---|---|---|---|---|
| PassengerId | 1.000 | 0.038 | -0.002 | 0.001 | 0.037 | 0.157 | 0.000 | 0.000 | 0.000 |
| Age | 0.038 | 1.000 | -0.223 | -0.269 | 0.168 | 0.101 | 0.312 | 0.115 | 0.104 |
| SibSp | -0.002 | -0.223 | 1.000 | 0.469 | 0.414 | 0.196 | 0.125 | 0.184 | 0.116 |
| Parch | 0.001 | -0.269 | 0.469 | 1.000 | 0.424 | 0.109 | 0.000 | 0.205 | 0.000 |
| Fare | 0.037 | 0.168 | 0.414 | 0.424 | 1.000 | 0.237 | 0.433 | 0.144 | 0.222 |
| Survived | 0.157 | 0.101 | 0.196 | 0.109 | 0.237 | 1.000 | 0.305 | 0.506 | 0.169 |
| Pclass | 0.000 | 0.312 | 0.125 | 0.000 | 0.433 | 0.305 | 1.000 | 0.057 | 0.302 |
| Sex | 0.000 | 0.115 | 0.184 | 0.205 | 0.144 | 0.506 | 0.057 | 1.000 | 0.111 |
| Embarked | 0.000 | 0.104 | 0.116 | 0.000 | 0.222 | 0.169 | 0.302 | 0.111 | 1.000 |
Dataset B
| PassengerId | Age | SibSp | Parch | Fare | Survived | Pclass | Sex | Embarked | |
|---|---|---|---|---|---|---|---|---|---|
| PassengerId | 1.000 | 0.075 | -0.009 | -0.027 | 0.023 | 0.064 | 0.000 | 0.000 | 0.000 |
| Age | 0.075 | 1.000 | -0.149 | -0.166 | 0.189 | 0.151 | 0.271 | 0.122 | 0.035 |
| SibSp | -0.009 | -0.149 | 1.000 | 0.519 | 0.439 | 0.150 | 0.103 | 0.240 | 0.106 |
| Parch | -0.027 | -0.166 | 0.519 | 1.000 | 0.412 | 0.140 | 0.042 | 0.300 | 0.000 |
| Fare | 0.023 | 0.189 | 0.439 | 0.412 | 1.000 | 0.263 | 0.431 | 0.208 | 0.159 |
| Survived | 0.064 | 0.151 | 0.150 | 0.140 | 0.263 | 1.000 | 0.307 | 0.543 | 0.139 |
| Pclass | 0.000 | 0.271 | 0.103 | 0.042 | 0.431 | 0.307 | 1.000 | 0.118 | 0.267 |
| Sex | 0.000 | 0.122 | 0.240 | 0.300 | 0.208 | 0.543 | 0.118 | 1.000 | 0.100 |
| Embarked | 0.000 | 0.035 | 0.106 | 0.000 | 0.159 | 0.139 | 0.267 | 0.100 | 1.000 |
Dataset A
A simple visualization of nullity by column.
Dataset B
A simple visualization of nullity by column.
Dataset A
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset B
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset A
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset B
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 55 | 56 | 1 | 1 | Woolner, Mr. Hugh | male | NaN | 0 | 0 | 19947 | 35.5000 | C52 | S |
| 202 | 203 | 0 | 3 | Johanson, Mr. Jakob Alfred | male | 34.0 | 0 | 0 | 3101264 | 6.4958 | NaN | S |
| 407 | 408 | 1 | 2 | Richards, Master. William Rowe | male | 3.0 | 1 | 1 | 29106 | 18.7500 | NaN | S |
| 797 | 798 | 1 | 3 | Osman, Mrs. Mara | female | 31.0 | 0 | 0 | 349244 | 8.6833 | NaN | S |
| 390 | 391 | 1 | 1 | Carter, Mr. William Ernest | male | 36.0 | 1 | 2 | 113760 | 120.0000 | B96 B98 | S |
| 313 | 314 | 0 | 3 | Hendekovic, Mr. Ignjac | male | 28.0 | 0 | 0 | 349243 | 7.8958 | NaN | S |
| 164 | 165 | 0 | 3 | Panula, Master. Eino Viljami | male | 1.0 | 4 | 1 | 3101295 | 39.6875 | NaN | S |
| 883 | 884 | 0 | 2 | Banfield, Mr. Frederick James | male | 28.0 | 0 | 0 | C.A./SOTON 34068 | 10.5000 | NaN | S |
| 51 | 52 | 0 | 3 | Nosworthy, Mr. Richard Cater | male | 21.0 | 0 | 0 | A/4. 39886 | 7.8000 | NaN | S |
| 332 | 333 | 0 | 1 | Graham, Mr. George Edward | male | 38.0 | 0 | 1 | PC 17582 | 153.4625 | C91 | S |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 263 | 264 | 0 | 1 | Harrison, Mr. William | male | 40.0 | 0 | 0 | 112059 | 0.0000 | B94 | S |
| 284 | 285 | 0 | 1 | Smith, Mr. Richard William | male | NaN | 0 | 0 | 113056 | 26.0000 | A19 | S |
| 142 | 143 | 1 | 3 | Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) | female | 24.0 | 1 | 0 | STON/O2. 3101279 | 15.8500 | NaN | S |
| 887 | 888 | 1 | 1 | Graham, Miss. Margaret Edith | female | 19.0 | 0 | 0 | 112053 | 30.0000 | B42 | S |
| 552 | 553 | 0 | 3 | O'Brien, Mr. Timothy | male | NaN | 0 | 0 | 330979 | 7.8292 | NaN | Q |
| 688 | 689 | 0 | 3 | Fischer, Mr. Eberhard Thelander | male | 18.0 | 0 | 0 | 350036 | 7.7958 | NaN | S |
| 315 | 316 | 1 | 3 | Nilsson, Miss. Helmina Josefina | female | 26.0 | 0 | 0 | 347470 | 7.8542 | NaN | S |
| 762 | 763 | 1 | 3 | Barah, Mr. Hanna Assi | male | 20.0 | 0 | 0 | 2663 | 7.2292 | NaN | C |
| 10 | 11 | 1 | 3 | Sandstrom, Miss. Marguerite Rut | female | 4.0 | 1 | 1 | PP 9549 | 16.7000 | G6 | S |
| 635 | 636 | 1 | 2 | Davis, Miss. Mary | female | 28.0 | 0 | 0 | 237668 | 13.0000 | NaN | S |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 393 | 394 | 1 | 1 | Newell, Miss. Marjorie | female | 23.0 | 1 | 0 | 35273 | 113.2750 | D36 | C |
| 718 | 719 | 0 | 3 | McEvoy, Mr. Michael | male | NaN | 0 | 0 | 36568 | 15.5000 | NaN | Q |
| 424 | 425 | 0 | 3 | Rosblom, Mr. Viktor Richard | male | 18.0 | 1 | 1 | 370129 | 20.2125 | NaN | S |
| 136 | 137 | 1 | 1 | Newsom, Miss. Helen Monypeny | female | 19.0 | 0 | 2 | 11752 | 26.2833 | D47 | S |
| 649 | 650 | 1 | 3 | Stanley, Miss. Amy Zillah Elsie | female | 23.0 | 0 | 0 | CA. 2314 | 7.5500 | NaN | S |
| 172 | 173 | 1 | 3 | Johnson, Miss. Eleanor Ileen | female | 1.0 | 1 | 1 | 347742 | 11.1333 | NaN | S |
| 323 | 324 | 1 | 2 | Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) | female | 22.0 | 1 | 1 | 248738 | 29.0000 | NaN | S |
| 218 | 219 | 1 | 1 | Bazzani, Miss. Albina | female | 32.0 | 0 | 0 | 11813 | 76.2917 | D15 | C |
| 767 | 768 | 0 | 3 | Mangan, Miss. Mary | female | 30.5 | 0 | 0 | 364850 | 7.7500 | NaN | Q |
| 864 | 865 | 0 | 2 | Gill, Mr. John William | male | 24.0 | 0 | 0 | 233866 | 13.0000 | NaN | S |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 423 | 424 | 0 | 3 | Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) | female | 28.0 | 1 | 1 | 347080 | 14.4000 | NaN | S |
| 763 | 764 | 1 | 1 | Carter, Mrs. William Ernest (Lucile Polk) | female | 36.0 | 1 | 2 | 113760 | 120.0000 | B96 B98 | S |
| 201 | 202 | 0 | 3 | Sage, Mr. Frederick | male | NaN | 8 | 2 | CA. 2343 | 69.5500 | NaN | S |
| 814 | 815 | 0 | 3 | Tomlin, Mr. Ernest Portage | male | 30.5 | 0 | 0 | 364499 | 8.0500 | NaN | S |
| 703 | 704 | 0 | 3 | Gallagher, Mr. Martin | male | 25.0 | 0 | 0 | 36864 | 7.7417 | NaN | Q |
| 75 | 76 | 0 | 3 | Moen, Mr. Sigurd Hansen | male | 25.0 | 0 | 0 | 348123 | 7.6500 | F G73 | S |
| 271 | 272 | 1 | 3 | Tornquist, Mr. William Henry | male | 25.0 | 0 | 0 | LINE | 0.0000 | NaN | S |
| 718 | 719 | 0 | 3 | McEvoy, Mr. Michael | male | NaN | 0 | 0 | 36568 | 15.5000 | NaN | Q |
| 349 | 350 | 0 | 3 | Dimic, Mr. Jovan | male | 42.0 | 0 | 0 | 315088 | 8.6625 | NaN | S |
| 512 | 513 | 1 | 1 | McGough, Mr. James Robert | male | 36.0 | 0 | 0 | PC 17473 | 26.2875 | E25 | S |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||